Predicting outcomes after hospitalisation for COPD exacerbation using machine learning
Applying machine learning techniques to large-scale data effectively improves the prediction of early readmission and death following ECOPD hospitalisation. Identifying critical prognostic factors could enhance targeted post-discharge care for this high-risk patient group.
Authors
- Chih‐Ying Wu (ORCID: https://orcid.org/0000-0002-7361-7840)
- Chien‐Ning Hsu (ORCID: https://orcid.org/0000-0001-7470-528X)
- Fang‐Ju Lin (ORCID: https://orcid.org/0000-0002-8249-7481)
- Charlotte Wang (ORCID: https://orcid.org/0000-0002-6957-1579)
- Jung‐Yien Chien (ORCID: https://orcid.org/0000-0002-7718-0594)
- Chi‐Chuan Wang (ORCID: https://orcid.org/0000-0002-4597-4859)
Institutions
- Kaohsiung Medical University (TW)
- National Taiwan University (TW)
- Kaohsiung Chang Gung Memorial Hospital (TW)
- National Taiwan University Hospital (TW)
Publication Details
- Journal
- ERJ Open Research
- Published
- 2024-10-31
- DOI
- https://doi.org/10.1183/23120541.00651-2024
- Citations
- 1
- Primary Topic
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Type
- article
- Field-Weighted Citation Impact
- 0.42
Funders
- National Science and Technology Council